A Study of the Dissemination of Malware and the Enhancement of the Lifespan of Rechargeable Wireless Sensor Networks: An Epidemiological Approach

Epidemic spreading in wireless sensor networks (WSNs) has lately attracted the attention of many researchers as a hot problem in nonlinear systems. Using wireless connectivity, the sensor nodes that makeup WSNs are linked to one another in a decentralized and distributed structure. Decentralized architectures and resource limitations pose a security risk for WSNs. Malware attacks the WSN’s sensor nodes, paralyzing them while collecting data from the network. Attacks by malware can increase the energy use of WSN sensor nodes. It just began spreading from one infected node and uses nearby nodes to expand over the whole WSN. Therefore, the protection of WSNs against malware attacks is a need that cannot be avoided. In this research paper, we propose an epidemic model to discuss the impact of charging on sensor nodes, coverage, and connectivity, considering prior research. The suggested model examines the dynamics of malware spread in WSNs and also explains how much energy is used by the sensor node. The stability of the system has been examined in terms of endemic and local equilibriums for malware propagation. The fundamental reproduction number expression, which is used to assess the prevalence of malware in WSN, has been calculated for the analysis of system dynamics. This study explains the implications of communication radius, sensor node charging, node density, and deployment area on malware dissemination. In comparison to previous models, the suggested approach offers a superior method to stop the propagation of malware in WSN. At the end, we show the results of a numerical simulation of how malware spreads, which proves that our theoretical approach is correct.